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The compute performance was quite low for 3.5TFlops, in F@H even beaten by 2070... I am wondering if it's again drivers/SW holding AMD back, like with Deep Lear
by bitL 8y ago
The compute performance was quite low for 3.5TFlops, in F@H even beaten by 2070... I am wondering if it's again drivers/SW holding AMD back, like with Deep Learning (in theory 15TFlops, in practice 7.5 etc.)
- dragontamer 8y agoNVidia's Turing cores are clearly more dynamic than AMD's. There are also driver issues for sure. ROCm and RadeonGPU-Pro (two different OpenCL implementations) have numerous differences in performance. ROCm 2.1 is still absolutely awful at Blender for example (definitely use RadeonGPU-PRO drivers for that instead). In some cases, I bet on Ahmdal's law. NVidia has fewer shaders at a higher clock than AMD. AMD's architecture is implicitly more parallel than NVidia's, so Ahmdal's law will hurt it (AMD's 4096 shaders on Vega64 will use more RAM than NVidia's 2304 CUDA shaders on the 2070). In others, it seems like AMD's drivers are still unoptimized. Something weird is going on with Blender's code and ROCm for example. -------- EDIT: I've seen some profiler data, and it seems like AMD's GPUs are rarely compute-ALU bound. They are often memory-bound. So AMD has far too strong compute for the graphics problems at hand. Alternatively, AMD's algorithms may be poorly tuned: they probably should be more compute heavy and try to use less RAM Bandwidth.
- throwaawyw 8y ago3.5 Tflops at double precision. The applied math/scientific computation people are going to love this.
- bitL 8y agoI was talking about FP64 ofc.